Use dropout among siblings and same-age intimates as risk markers to target prevention resources and monitoring¶

Strategy · All strategies
Evidence · 6 claims (6 for) · 1 study (1 associational), q3 · 1 of 1 report an effect size · 6 claims rest on one study

Description¶

The authors recommend using occurrences of dropout among an adolescent's same-age intimates as markers of elevated risk for allocating intervention resources. Sibling dropout information is "readily available to school administrators and can thus be integrated into existing monitoring systems" designed to flag students at elevated risk in upcoming months. School staff such as psychologists and teachers involved in extra-curricular activities can suggest prevention intervention for students who are friends or romantic partners of recent dropouts.

Design Implications¶

Context¶

Requirements¶

• School administrative data linking students to siblings, and staff informed about students' social lives

Constraints¶

• Fluctuating friendships and romantic relationships are much more difficult to track than sibling information
• The non-experimental findings do not conclusively demonstrate that social contagion is a cause of dropout

Target Learners¶

• High school adolescents in low-income schools

Target Learning Goals¶

• High school perseverance and dropout prevention

Claims¶

• Only recent (within the past year) occurrences of dropout in an adolescent's network are associated with the adolescent's own dropout; older occurrences are not [+M]
• Dropout among friends, romantic partners, and siblings each shows an independent association with an adolescent's own dropout [+M]
• Risk of dropout is especially high when an adolescent's network includes more than one type of same-age intimate who recently dropped out [+M]
• Adolescents are at greater risk of dropping out when at least one same-age intimate (friend, romantic partner, or sibling) has recently dropped out of school [+M]
• The main dropout-contagion findings remained essentially unchanged across five robustness checks including unmatched samples, IPTW, and conditional regression [+M]
• The association between network dropout and adolescents' own dropout does not significantly differ by gender or by regular versus special education sector [+W]

Related Strategies¶

• Use an early warning system based on linked school and human services data to target resources and lessen risks before they become more serious
• Use school-level data systems to identify which students need which types of support for dropout prevention

Examples¶

-

Key Sources¶

• Dupéré, V., Dion, E., Cantin, S., Archambault, I., & Lacourse, E. (2021). Social contagion and high school dropout: The role of friends, romantic partners, and siblings. Journal of Educational Psychology, 113, 572-584. https://doi.org/10.1037/edu0000484